Despite extensive expenditures of money and effort in the healthcare industry, evidence-based practices are often slow to diffuse from the settings in which they were initially developed.1 Differential adoption rates can result in significant disparities in the quality and costs of care provided. In trying to decrease this variation, evidence-based practices as they are originally conceived may not be well equipped to spread to other organizations.10, 11 Since pilot interventions are usually tested in innovative organizations, 11 the lessons learned from initial implementation may not be directly applicable to organizations later in the adoption process, which might behave very differently from those early innovators. Little is known about the factors influencing physician organizations' adoption of evidence-based practices for chronic care conditions, and more specifically how past adoption efforts may affect future adoption choices. Past literature tends to focus on high performers, creating a dearth of information on later adopters.7, 14 this proposed dissertation seeks to address these gaps. This proposed dissertation would use data from the 2012-2013 National Survey of Physician Organizations (NSPO), a survey that collected data describing the organizational characteristics of physician organizations across the United States, including adoption of evidence-based practices with a specific focus on four key chronic illnesses (asthma, congestive heart failure, depression, and diabetes). This proposed dissertation will use an explanatory sequential mixed methods design2 to examine organizational factors influencing physician organizations' adoption of evidence-based practices for chronic care conditions. The proposed research will occur in two sequential phases. In Phase I, quantitative data analyses of the data set will address the first three Aims: 1) explore the adoption patterns of evidence-based practices using scale analysis; 2) Identify organizational characteristics associated with non-adoption using a two-part model; and 3) Identify the characteristics of positive deviants who have adopted practices despite sharing similar characteristics with non-adopters by calculating predicted probabilities of adoption and contrasting the predictions with actual adoption choices. In Phase II, qualitative data analysis of semi- structured interviews at both positive deviant and low adopting physician organizations will address Aim 4: Explore the role of culture, leadership, and organizational priorities in the decision to adopt evidence-based practices. Three key informants from four positive deviants and four low adopter physician organizations will provide data for template analysis. If the milieu of factors influencing adoption patterns are better understood, especially in low adopting practices, better strategies for evidence-based practice uptake can be crafted and disseminated.